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Wednesday, 11 December 2013

No doubt, after the Snowden revelations and the recent
confrontation between Germany and the US, several citizens will be asking
themselves whether their private communications are under surveillance, and to
what extent. This very event has triggered intensive debate in the media and in
the political arenas of several European countries not only about the extent
and purpose of the surveillance programs, but also about one of the
technologies that are being used to arrange such surveillance: that is Big Data.
Big data is high-volume, high-velocity and high-variety information assets that
demand cost-effective, innovative forms of information processing for enhanced
insight and decision-making.[2]

It must be acknowledged that there are different ways of
using Big Data, and that the application of this set of technologies does not
necessarily need to be oriented towards the surveillance of individual
citizens. For instance, data can be anonymised, which allows research to be
conducted and data to be extracted and analyzed without preserving any link
between the data and the citizens to whom these data are related.

Is technology neutral?

However, this is not equal to saying that Big Data is a
neutral technology. Any technology, regardless of how many uses it may have, is
never neutral. Technologies, or rather sociotechnical practices, can never be
understood as stand alone pieces of human art crafts because they only work and
make sense in a network of socially constructed meanings, practices,
organizational protocols and tailor-made jargons. They come with their own
ethics, their own values. These values reflect the dominant political
priorities and ethical values of the societal stakeholders producing and using
such technologies. They may indeed change over time, but they will do so along
with the changes occurring in the society adopting, sustaining and implementing
such sociotechnical practices.

This is, in a few words, the basic assumption proposed by
what is known as a co-production approach in science and technology studies [3]:
science and social order are co-produced and they live in a mutually
constitutive relationship. Producing new scientific knowledge, as well as the
new technological tools stemming from such knowledge, produces new forms of
social order, and the opposite is also true: in order to produce new forms of
social order, new knowledge and technical tools are constantly fabricated.

Of cars and Big Data

An example, perhaps, may illustrate this better. If asked
about the cost of a specific car, we would normally answer by pointing at the
price of that car. But that is hardly the actual cost… or better that is the
cost only if seen from a specific point of view, which externalizes all the
real costs of a car and narrows the question down to the transaction between
the car dealer and the potential customer. However, cars, as a technology, only
make sense as part of a sophisticated network of sociotechnical practices that
needs to be constantly maintained to ensure that cars can fully operate across
a given space. Cars need roads, police, laws, speed cameras, hospital, doctors,
insurance companies, mechanics, gasoline pumps, etc. Without these
sociotechnical infrastructures and practices, a car is simply a meaningless,
useless box with five seats and four wheels. All these infrastructures have a
cost and we accept that most of these costs are to be paid collectively by the
citizens, often via the public system of tax collection. And why do we do so?
Because we believe that cars are a socially legitimate way to move around.

If that is true for cars, it is even more so for Big Data.
The latter, as a sociotechnical practice of security, only can be understood in
a society that understands security as a function of surveillance. This is why,
in so far as security is concerned, Big Data could never be anonymised as it
would not make sense to have millions of data proceeding from harmless
citizens’ communication without having name and surname (and much more) on it.
The question, thus, is not whether we are spied or not, but rather: how did we
come to pursue a concept of security, where many seem to believe that the
latter can only be increased through massive surveillance programs operated
through Big Data technologies?

A paradigm shift concept of security?

While in the 1990s, human security was associated with human
development, human rights and multilateralism, in the aftermath of the Twin
Towers attack it has evolved into a new, encompassing term that questions the
separation between internal and external security: religious fundamentalism,
ethnic conflicts and guerrilla-type wars are sources of threats that can well
come from inside the state borders [4]. As a result, internal and external
security agendas have eventually merged together [5]. Drug-trafficking, undocumented migration, and
economic crimes cease to be an issue of justice or social integration and,
overloaded with urgency and exceptionality, get subject to a new security
approach emphasizing threat anticipation.

In a regime of threat anticipation, risk assessment and risk
management become the cornerstone of a comprehensive approach that is geared to
constant detection and prevention of the threats and risks. In this new
approach, security is expanded well beyond the criminal domain in order to cope
with any sort of suspicious behavior, information or action that could
potentially constitute a threat. The resulting securitization of people’s
movements and actions cannot be confined to migrants: under the new concept of
security, controlling and integrating all sorts of information about ordinary
citizens is nothing but inexorable.

The constitutive role of security technologies

In this approach to security, surveillance-oriented security
technologies, and the analysis of Big Data is one of them, play a constitutive
role: they are part of a new social order. As it has become impossible to
conceive security without technology, we are permanently exposed to a
technological fix approach to the problem of security: the focus constantly
shifts from the search for a (complex) variety of causes and factors that has
produced the on-going transformation of security threats to (simple) series of
technological remedies that could be conceived, developed and implemented to
keep these challenges under control.

Inevitably, the successful deployment of new security
technologies under this new holistic concept of security comes at a cost: a
restriction of civil liberties and individual privacy. Security and liberty get
framed as two interchangeable goods that could be traded against each other:
any increase in security requires an equivalent contraction of civil liberties.
As the increase of security levels is intrinsically associated with an
ever-increasing implementation of surveillance technologies, it does not
consider the possibility of increasing security levels through either
non-surveillance-oriented technologies or through non-technological actions and
interventions.

Without freedom, we are no longer citizens

This is how we got to the point where millions of citizens
around the world are spied indiscriminately. However, once we have lost our
privacy, we can no longer act, meet, communicate, share or express ourselves
freely. Under surveillance, regardless of whether we have something to hide or
not, we cannot enjoy our basic civil and political rights. It is in this
context that we have to understand Big Data. They are key to the development
and implementation to a specific vision of what needs to be promoted as social
order. Needless to say, this specific view of a desirable social order is at
the same time promoting and fostering the development and implementation of Big
Data.

This is why developing such powerful technologies and then
hope that a few parliamentary bills will prevent their full implementation is
wishful thinking. Rather, we need to learn to conceive security in different
terms, as a shared responsibility and not only a function of repressive and
preventive surveillance. Social and economic factors such as social and
cultural integration, welfare supports, rule of law, fair redistribution of
resources and citizens’ participation are at least as important. We often hear
that without security, citizens cannot be free. Sure, this is true. However, without
freedom, no matter how safe, we are no longer citizens.

Tuesday, 15 October 2013

Guest post from ALBERT-LÁSZLÓ BARABÁSI

The recent revelation that the
National Security Agency collects the personal data of United States citizens,
allies and enemies alike has broken the traditional model governing the bond
between science and society.

Most breakthrough technologies
have dual uses. Think of atomic energy and the nuclear bomb or genetic engineering
and biological weapons. This tension never gives way. Our only hope to
overcoming it is to stop all research.

But that is unrealistic. Instead,
the model we scientists follow is simple: We need to be transparent about the
potential use and misuse of our trade. We publish our results, making them
accessible to everyone. And when we do see the potential for abuse, we speak
up, urging society to reach a consensus on how to keep the good but outlaw the
bad.

As the NSA secretly developed its
unparalleled surveillance program, relying on a mixture of tools rooted in
computer and social sciences, this model failed. Scientists whose work fueled
these advances failed to forcefully articulate the collateral dangers their
tools pose. And a political leadership, intoxicated by the power of these
tools, failed to keep their use within the strict limits of the Constitution.

It’s easy to see why this
happened. After all, the benefits of Big Data and the science behind it are
hard to overlook. Beyond the many digital applications that make our life
increasingly easy today, data science holds promise for emergency response and
for stopping the next virus from turning into a deadly pandemic. It also holds
the key to our personal health, since our activity patterns and disease history
are more predictive of our future disease than our genes.

For researchers involved in basic
science, like myself, Big Data is the Holy Grail: It promises to unearth the
mathematical laws that govern society at large. Motivated by this challenge, my
lab has spent much of the past decade studying the activity patterns of
millions of mobile phone consumers, relying on call patterns provided by mobile
phone companies. This data was identical to what NSA muscled away from
providers, except that ours was anonymized, processed to help research without
harming the participants. In a series of research papers published in the
journals Science and Nature, my team confirmed the promise of Big Data by
quantifying the predictability of our daily patterns, the threat digital
viruses pose to mobile phones and even the reaction people have when a bomb
goes off beside them.

We also learned that when it
comes to our behavior, we can’t use only two scales — one for good and the
other for bad. Rather, our activity patterns are remarkably diverse: For any
act labeled “unusual” or “anomalous,” such as calling people at odd hours or
visiting sensitive locations outside our predictable daily routine, we will
find millions of individuals who do just that as part of their normal routine.
Hence identifying terrorist intent is more difficult than finding a needle in a
haystack — it’s more like spotting a particular blade of hay.

Let’s face it: Powered by the
right type of Big Data, data mining is a weapon. It can be just as harmful,
with long-term toxicity, as an atomic bomb. It poisons trust, straining
everything from human relations to political alliances and free trade. It may
target combatants, but it cannot succeed without sifting through billions of
data points scraped from innocent civilians. And when it is a weapon, it should
be treated like a weapon.

To repair the damage already
done, we researchers, with a keen understanding of the promise and the limits
of our trade, must work for a world that uses science in an ethical manner. We
can look at the three pillars of nuclear nonproliferation as a model for going
forward.

The good news is that the first
pillar, the act of nonproliferation itself, is less pertinent in this context:
Many of the technologies behind NSA’s spying are already in the public domain,
a legacy of the openness of the scientific enterprise. Yet the other two
pillars, disarmament and peaceful use, are just as important here as they were
for nuclear disarmament. We must inspect and limit the use of this new science
for military purposes and, to restore trust, we must promote the peaceful use
of these technologies.

We can achieve this only in
alliance with the society at large, together amending universal human rights
with the right to data ownership and the right of safe passage.

Data ownership states that the
data pertaining to my activity, like my browsing pattern, shopping habits or
reading history, belongs to me, and only I control its use. Safe passage is the
expectation that the information I choose to transfer will reach its intended
beneficiaries without being tapped by countless electronic ears along the way.
The NSA, by indiscriminately tapping all communication pipelines, has degraded
both principles.

Science can counteract spying
overreach by developing tools and technologies that, by design, lock in these
principles. A good example of such a design is the Internet itself, built to be
an open system to which anyone could connect without vetting by a central
authority. It took decades for governments around the world to learn to censor
its openness.

This summer, while visiting my
hometown in Transylvania, I had the opportunity to talk with a neighbor who
spent years as a political prisoner. Once freed, for decades to come, he knew
that everything he uttered was listened to and recorded. He received
transcripts of his own communications after the fall of communism. They spanned
seven volumes. It was toxic and dehumanizing, a way of life that America has
repeatedly denounced and fought against.

So why are we beginning to spread
communism 2.0 around the world, a quarter-century after the Iron Curtain’s
collapse? This is effectively what NSA surveillance has become. If we
scientists stay silent, we all risk becoming digitally enslaved. Posted with permission.

Albert-László Barabási is a
physicist and network scientist at Northeastern University and Harvard Medical
School, and the author of “Bursts: The Hidden Patterns Behind Everything We
Do.”

Wednesday, 11 September 2013

The Internet
and Social Media change our way of decision-making. We are no longer the
independent decision makers we used to be. Instead, we have become networked
minds, social decision-makers, more than ever before. This has several fundamental
implications. First of all, our economic theories must change, and second, our
economic institutions must be adapted to support the social decision-maker, the
"homo socialis", rather be tailored to the perfect egoist, known as
"homo economicus".

The financial, economic and public debt crisis has seriously damaged
our trust in mainstream economic theory. Can it really offer an adequate
description of economic reality? Laboratory experiments keep questioning one of
the main pillars of economic theory, the "homo economicus". They show
that the perfectly self-regarding decision-maker is not the rule, but rather
the exception [1,2]. And they show that markets, as they are organized today,
are undermining ethical behavior [3].

Latest scientific results have shown that a "homo socialis"
with other-regarding preferences will eventually result from the merciless
forces of evolution, even if people optimize their utility, if offspring tend
to stay close to their parents [4]. 1Another,
independent study was recently summarized by the statement "evolution will
punish you, if you're selfish and mean" [5]. Is this really true? And what
implications would this have for our economic theory and institutions?

In fact, the success of the human species as compared to others
results mainly from its social nature. There is much evidence that evolution
has created different incentive systems, not just one: besides the desire to possess
(in order to survive in times of crises), this includes sexual satisfaction (to
ensure reproduction), curiosity and creativity (to explore opportunities and
risks), emotional satisfaction (based on empathy), and social recognition
(reputation, power). Already Adam Smith noted: "How ever selfish man
may be supposed, there are evidently some principles in his nature, which
interest him in the fortune of others, and render their happiness necessary to
him, though he derives nothing from it."2

Dirk Helbing, professor of sociology at ETH Zurich and complexity
scientist concludes: "The social nature of man has dramatic implications,
both for economic theory and for the way we need to organize our economy."
As we are more and more connected with others, the "homo economicus",
i.e. the independent decision-maker and perfect egoist, is no longer an
adequate representation or good approximation of human decision-makers. "Reality
has changed. We are applying an outdated theory, and that's what makes economic
crises more severe," says Helbing.

Outdated
theory, outdated institutions

In fact, recent experimental results suggest that the majority of
decision-makers are of the type of a "homo socials" with equity- or
equality-oriented fairness preferences [1,6]. The "homo socialis" is
characterized by two features: interdependent decision-making that takes into
account the impact on others and conditional cooperativeness. However, the
"homo socialis" takes self-determined, free decisions. He is not
ripping off others, afterwards giving back some of the benefits to others
through taxes or philanthropy. The "homo socialis" decides rather differently,
more considerately, recognizing that friendly and fair behavior can generate
better outcomes for everybody.

"But social behavior is vulnerable to exploitation by the 'homo
economicus'," continues Helbing. In a selfish environment, the 'homo
socialis' cannot thrive. In other words, if the settings are not right, the
'homo socialis' behaves the same as the 'homo economicus'. "That's probably
why we haven't noticed its existence for a long time," believes Helbing.
"Our theories and institutions were tailored to the 'homo economicus', not
to the 'homo socialis'."

In fact, many of today's institutions, such as homogeneous markets
with anonymous exchange, undermine cooperation in social dilemma situations,
i.e. situations in which cooperation would be favorable for everyone, but
non-cooperative behavior promises additional benefits [7, Fig. 2].

New
institutions for a global information society

In the past we have built public roads, parks and
museums, schools, libraries, universities, and homogeneous markets on a global
scale. What would be suitable institutions for the 21st century? "Reputation
systems can transfer the success principles of social communities to our
globalized society, the global village", suggests Helbing. Most people and
companies care about reputation. Therefore, reputation systems could support socially
oriented decision-making and cooperation, with better outcomes for everyone [8].
In fact, reputation systems spread on the Web 2.0 like wildfire. People rate
products, sellers, news, everything, be it at amazon, ebay, or trip adviser. We
have become a "like it" generation, because we listen to what our
friends like.

Importantly, recommender systems should not narrow down
socio-diversity, as this is the basis of happiness, innovation and societal
resilience. "We don't want to live in a filter bubble, where we don't get
an objective picture of the world anymore," says Helbing with reference to
Eli Pariser [9]. Therefore, reputation systems should be pluralistic, open, and
user-centric. "Pluralistic reputation systems are oriented at the values
and quality criteria of individuals," explains Helbing, "rather than
recommending what a company's reputation filter thinks is best. Self-determination
of the user is central. We must be able to use different filters, choose the
filters ourselves, and modify them." The diverse filters would mine the
ratings and comments that people leave on the Web, but also consider how much
one trusts in certain information sources.

"Reputation creates benefits for buyers and sellers," says
Helbing. A recent study shows that good reputation allows sellers to take a
higher price, while customers can expect a better service [10]. Reputation
systems may also promote better quality as well as socially and environmentally
friendly production, suggests Helbing. "This could be a new approach to
reach more sustainable production, based on self-regulation rather than
enforcement by laws." One day, reputation systems may also be used to
create a new kind of money, speculates Helbing. The value of "qualified
money" would depend on it's reputation and thereby create incentives to
invest in ways that increase a money unit's reputation. It might create a more
adaptive financial system and help to mitigate the recurrent crises we are
facing since hundreds of years. But the details still have to be worked out.

Benefits of a
self-regulating economy

Reputation systems could overcome some of the unwanted side effects
of anonymous exchange thanks to pseudonymous or personal interactions. Thereby,
they could potentially counter "tragedies of the commons" such as global
warming, environmental exploitation and degradation, overfishing, .. -
constituting some of our major unsolved global problems. We can witness such
kinds of "social dilemma problems" everywhere. So far, governments
try to fix them with top-down regulations and punitive institutions. However,
these are very expensive, and often quite ineffective. "Basically all
industrialized countries suffer from exploding debts," says Helbing.
"I believe we cannot pay for this much longer, we are at the limit. We
need a new approach." As Albert Einstein pointed out: "We cannot solve
our problems with the same kind of thinking that created them."

Institutions supporting the "homo socialis" such as
suitably designed reputation systems would enable a self-regulation of
socio-economic systems. "But self-regulation does not mean that everyone
can choose the rules he likes," explains Helbing. "It only works with
an other-regarding element. The self-regulation rules must be able to achieve a
balance between the interests of everyone, who is affected by the externalities
of a decision."

Helbing explains the benefits: "Other-regarding decisions can
overcome the classical conflict between economic and social motives.
Self-regulation could also overcome the struggle between the bottom-up
organization of markets and the top-down regulation by politics. This would
remove a lot of friction from our current system, making it much more efficient
- in the same way as the transition from centrally planned economies to
self-organized markets has often created huge efficiency gains."

This can be illustrated with an example from urban traffic
management. "Traffic control is a problem where not everybody's desires
can be satisfied immediately and at the same time, like in economic systems. It
is a so-called NP-hard optimization problem - the computational effort explodes
with system size, as for many economic optimization problems, e.g. in
production and logistics." The study compares three kinds of control: A
centralized top-down regulation by a traffic center, the classical control
approach, and two decentralized control approaches. The first one assumes that
each intersection independently minimizes the waiting times of approaching
vehicles, as a "homo economicus" would do. The second one decides in
an other-regarding way: it interrupts the minimization of waiting times, when
this is needed to avoid spill-over effects at neighboring intersections.
Helbing summarizes: "The 'homo economicus' approach works well up to a
moderate utilization of intersections, but queue lengths get out of control long
before the intersection capacity is reached. The bottom-up self-regulation
based on the principle of the 'homo socialis' approach beats both, the
centralized top-down regulation and the bottom-up self-organization based on
principles of the 'homo economicus'. Other-regarding behavior improves the
coordination among neighboring intersections. It makes Adam Smith principle of
the 'invisible hand' work even at high utilizations."

Economics 2.0:
Emergence of a participatory market society

But will such a self-regulating system ever be implemented? Helbing
is convinced: "It's already on its way. The Web 2.0, in particular
reputation systems and social media are driving the transition towards a new
economy, the economy 2.0. We see already a new trend towards decentralized,
local production and personalized products, enabled by 3D printers, app stores,
and other technologies."

Such developments will eventually create a participatory market
society. "Prosumers", i.e. co-producing consumers, the new
"makers" movement, and the sharing economy are some examples
illustrating this. "Just think of the success of Wikipedia, Open Streetmap
or Github. Open Streetmap now provides the most up-to-date maps of the world,
thanks to more than 1 million volunteers." Helbing stresses: "This is
just the beginning of a new era. A new intellectual framework is emerging, and
a creative and participatory era is ahead. The paradigm shift towards
participatory bottom-up self-regulation may be bigger than the paradigm shift
from a geocentric to a heliocentric worldview. If we build the right
institutions for the information society of the 21st century, we will finally
be able to mitigate some very old problems of humanity. 'Tragedies of the
commons' are just one of them. After so many centuries, they are still plaguing
us, but this needn't be."

[1]Experts should note that there has been research on so-called "altruistic behavior" in social dilemma situations such as the prisoner's dilemma since more than 3 decades. However, if scientists would have understood the "homo socialis" with other-regarding preferences already before, the key concept of the "homo economicus" should have disappeared from the economic literature since a long time, but it didn't for a reason. In fact, the increasing empirical and experimental evidence for fairness preferences and unexpectedly high levels of cooperation in one-shot prisoner's dilemma, dictator and ultimatum games have been waiting for a convincing theoretical explanation until very recently. It is important here to distinguish between other-regarding preferences and cooperative ("altruistic") behavior. Other-regarding preferences means that people intentionally do not maximize their payoffs, but try to consider and improve the benefits of others. Most game theoretical work is strictly compatible with the concept of "homo economicus", identifying mechanisms that make it advantageous in one way or another to cooperate. For example, if the "shadow of the future" in repeated prisoner's dilemma interactions is long enough, it creates a higher payoff when people cooperate, and that's why they do it. In other words, some mechanisms such as repeated interactions, punishment, transfer payments, and others change the payoff structure of a prisoner's dilemma game such that there is no dilemma anymore. Martin Nowak has mathematically shown that many such mechanisms can be understood with Hamilton's rule, according to which people cooperate when the benefits of cooperation exceed the costs. Other work shows that cooperation in prisoner's dilemma games may survive if people imitate more successful behavior of neighbors, but if one believes in rational choice, why should people imitate, if they can reach a higher payoff by another behavior? In fact, all such cooperation in spatial prisoner's dilemma games disappears, if imitation is replaced by a "best response" rule, which assumes a strict maximization of utility, based on the previous decision of the interaction partners. In Ref. [4], Grund et al. have combined such a "best response" rule with standard evolutionary rules of mutation and selection, when people reproduce. The unexpected outcome was a "homo socialis", if offspring stay close to their parents, which they often do. But the transition is not smooth. It requires the population to go through a phase where unconditionally "friendly" behavior is dysfunctional, which happens only by "mistake" (due to mutations). Random spatio-temporal coincidence of people with friendly traits is equally important for other-regarding preferences to emerge. However, conditionally cooperative behavior resulting from other-regarding preferences may also occur between strangers, i.e. they do not require genetic relatedness, as the following movie shows: http://vimeo.com/65376719. In any case, spatio-temporal correlations (here: the co-evolution of individual preferences and behavior) can promote cooperation more than expected for a payoff-maximizing "homo economicus". These new discoveries mean that key concepts of both, the theory of evolution and of economics, must be reconsidered.

[10] Przepiorka, W., "Buyers pay for and sellers invest in a good
reputation: More evidence from eBay,'' The Journal of Socio-Economics 42, 31-42
(2013).

Dirk
Helbing is Professor of Sociology, in particular of
Modeling and Simulation, and member of the Computer Science Department at ETH
Zurich. He earned a PhD in physics and was Managing Director of the Institute
of Transport & Economics at Dresden University of Technology in Germany. He
is internationally known for his work on pedestrian crowds, vehicle traffic,
and agent-based models of social systems. Furthermore, he coordinates the FuturICT
Initiative (http://www.futurict.eu),
which focuses on the understanding of techno-socio-economic systems, using Big
Data. His work is documented by hundreds of scientific articles, keynote
lectures and media reports worldwide. Helbing is elected member of the World
Economic Forum’s Global Agenda Council on Complex Systems and of the German
Academy of Sciences “Leopoldina”. He is also Chairman of the Physics of
Socio-Economic Systems Division of the German Physical Society and co-founder
of ETH Zurich’s Risk Center.

Tuesday, 9 July 2013

by Dirk Helbing (ETH Zurich)

Our society is
changing. Almost nothing these days works without a computer chip; computing
power doubles every 18 months, and in ten years it will probably exceed the
capabilities of a human brain. Computers perform approximately 70 percent of
all financial transactions today and IBM's Watson now seems to give better
customer advise than some human telephone hotlines.

The forthcoming
economic and social transformation might be more fundamental than the one
resulting from the invention of the steam engine. Meanwhile, the storage
capacity of data grows even faster than the computational capacity. Within a
few years, we will generate more data than in the entire history of humankind. The
"Internet of Things" will soon network trillions of sensors together
- fridges, coffee machines, electric toothbrushes and even our clothes. Vast
amounts of data will be collected. Already, Big Data is being heralded as the
oil of the 21st Century.

But this situation
will also make us vulnerable. Exploding cyber-crime, economic crises and social
protests show that our hyper-connected world is destabilizing. However, is a Surveillance
Society the right answer? When all our Internet queries are stored, when our
purchases and social contacts are evaluated, when our emails and files are
scanned for search terms, and when countless innocent citizens are classified
as potential future terrorists, we must ask: Where will this lead to? And where
will it end?

Will surveillance lead
to self-censorship and discrimination against intellectuals and minorities, even
though innovation and creative thinkers are bitterly needed for our economy and
society to do well in our changing world? Will free human expression eventually
be curtailed by data mining machines analyzing our digital trails?

What are the
consequences, say if even the Swiss banks and the U.S. government can no longer
protect their secrets, or if our health and other sensitive data is sold on? Or
if politically and commercially sensitive strategies can be monitored in real
time? What if insider knowledge can be used to undermine fair competition and
justice?

The recent
allegations that information agencies of various states snoop secretly into the
activities of millions of ordinary people has alarmed citizens and companies alike.
The moral outrage in response to the surveillance activity has made it clear that
it is not a technology-driven society that we need, but instead, a socially-oriented
technology, as outlined below. We must recognize that technology without
consideration of ethical issues, or without transparency and public discussions
can lead us astray. Therefore a new approach to personal data and its uses is required
so that we can safely benefit from the many new economic and social
opportunities that it can provide.

First, we need a
public ethical debate on the concepts of privacy and ownership of data, even
more urgently than in bioethics. Important questions that we have to ask are: How
do we create opportunities arising in the information age for all, but yet still
manage the downside risks and challenges - from cyber-crime to the erosion of trust
and democratic rights? Do we really need so much security that we must be
afraid of data mining algorithms flagging the activities of millions of ordinary
people as suspicious? And what kinds of new institutions would we need in the
21 century?

In the past we
have built public roads, parks and museums, schools, libraries and universities.
Now, more than ever, we need strategies that protect us against the misuse of
data, and that are intended to create transparency and trust. These strategies must
place citizen benefits and rights of self-determination at the very core. In
addition, we must develop new institutions to provide oversight and control of the
new challenges brought by the data revolution. Here are some concrete institutional
proposals:

Self-determined use of personal data: Already
some time ago, the World Economic Forum (WEF) called for a "New Deal on Data". It stated that the sustainable use of the economic
opportunities of personal data requires a fair balance between economic,
governmental and individual interests. A solution would be to return control
over personal data to the respective individuals, i.e. give people ownership of
their data: the right to possess, access, use and dispose. In addition, individuals
should be able to participate in their economic profits. This would require new
data protocols and the support of legislation.

Trusted information exchange: As
the vulnerability of existing systems and the proliferation of cyber-crime indicates,
a new network architecture is urgently needed. The handling of sensitive data
requires secure encryption, anonymisation and protected pseudonyms,
decentralized storage, open software codes and transparency on the use of data,
correction possibilities, mechanisms of forgetting, and a protective "digital
immune system."

Credibility mechanisms: Social
mechanisms such as reputation, as seen in the evaluation of information and
information sources on the internet, can play a central role in reducing abuse.
But remember that the wisdom of crowds only works if individual decisions are
not manipulated. Therefore, to be effective, individuals must be given control
over the recommendation mechanisms, data filtering and search routines they use,
such that they can take decisions based on their own values and quality
criteria.

Participatory platforms: All
over the world people desire increased participation, from consumption to production
processes. Now, modern technology allows for the direct social, economic, and
political participation of engaged individuals. A basic democracy approach as
in Switzerland, where people can decide themselves about many laws, not just
political representatives, would be feasible on much larger scales. We also
witness an economic trend towards local production, ranging from solar panels
to 3D Printers. It can be become a good complement of mass production.

Open Data: The innovation ecosystem needs open data and open
standards to flourish. Open data enable the rapid creation of new products,
which stimulates further products and services. Information is the best
catalyst for innovation. Of course, data providers should be adequately
compensated, and not all data would have to be open.

Innovation Accelerator: To keep pace with
our changing world, we need to reinvent the innovation process itself. A participatory
innovation process would allow ideas to be implemented faster and external
expertise to be integrated more readily. Information is an extraordinary resource:
it does not diminish when shared, and it can be infinitely reproduced. Why shouldn't we use this opportunity?

Social Capital: Information systems can support diverse types of social
capital such as trust, reputation, and cooperation. Based on social network
interactions, they are the foundation of a flourishing economy and society. So,
let's create new value!

Social Technologies: Finally, we must
learn to build information systems that are compatible with our individual,
social and cultural values. We need to design systems that respect the privacy
of citizens and prevent fear and discrimination, while promoting tolerance,
trust, and fairness. What solutions can we offer users to ensure that information
systems are not misused for unjustified monitoring and manipulation? For a well-functioning
society, socio-diversity (pluralism) must be protected as much as biodiversity.
Both determine the potential for innovation.

These are just
some examples of the promising ways in which we could use the Internet of the
future. Among all these, a surveillance society is probably the worst of all
uses of information technology. A safe and sustainable information society has
to be built on reputation, transparency and trust, not mass surveillance.

If we can no
longer trust our phones, computers or the Internet, we will either switch off
our equipment or start to behave like agents of a secret service: revealing as
little information as possible, encrypting data, creating multiple identities,
laying false traces.

Such behaviour
would create little benefits for ordinary citizens, besides protection, but
might help criminals to hide. It would be a pity if we failed to use the
opportunities afforded by the information age, just because we did not think
hard or far enough about the technological and legal frameworks and
institutions needed.

The information
age is now at a crossroad. It may eventually lead us to a totalitarian
surveillance state, or we can use it to enable a creative, participatory
society. It is our decision, and we should not leave it to others.

It is
also time to build the institutions for the globalized information society to
come, in a world-wide collaboration, instead of starting a global war of
information systems.

Thursday, 27 June 2013

by Dirk Helbing (ETH Zurich, dhelbing@ethz.ch)These days, it is often
claimed that we need massive surveillance to ensure a high level of security.
While the idea sounds plausible, I will explain, why this approach cannot work
well, even when secret services have the very best intentions, and their
sensitive knowledge would not be misused. This is a matter of statistics - no
method is perfect.

For the sake of illustration,
let us assume there are 2000 terrorists in a country with 200 Mio. inhabitants.
Moreover, let us assume that the secret service manages to identify terrorists
with an amazing 99% accuracy. Then, there are 1% false negatives (type II
error), which means that 20 terrorists are not detected, while 1980 will be
caught. The actual numbers are much smaller. It has been declared that 50
terror acts were prevented in about 12 years, while a few terrorist attacks
could not be stopped (although the terrorists were often listed as suspects).

It is also important to ask,
how many false positives ("false alarms") do we have? If the type I
error is just 1 out of 10,000, there will be 20,000 wrong suspects, if it is 1
permille, there will be 200,000 wrong suspects, and if it is 1 percent, it will
be 2 million false suspects. Recent figures I have heard of on TV spoke of 8
Million suspects in the US in 1996, which would mean about a 4 percent error
rate. If these figures are correct, this would mean that for every terrorist,
4000 times as many innocent citizens would be wrongly categorized as
(potential) terrorists.

Hence, large-scale
surveillance is not an effective means of fighting terrorism. It rather tends
to restrict the freedom rights of millions of innocent citizens. It is not
reasonable to apply surveillance to the whole population, for the same reasons,
why it is not sensible to make a certain medical test with everybody. There
would be millions of false positives, i.e. millions of people who would be
wrongly treated, with negative side effects on their health. For this reason,
patients are tested for diseases only if they show worrying symptoms.

In the very same way, it
creates more harm than benefit, if everybody is being screened for being a
potential future terrorist. This will cause unjustified discrimination and
harmful self-censorship at times, where unconventional, new ideas are needed
more than ever. It will impair the ability of our society to innovate and
adapt, thereby promoting instability. Thus, it is time to pursue a different
approach, namely to identify the social, economic and political factors that
promote crime and terrorism, and to change these factors. Just 2 decades back,
we saw comparatively little security problems in most modern societies.
Overall, people tolerated each other and coexisted peacefully, without massive
surveillance and policing. We were living in a free and happy world, where
people of different cultural backgrounds respected each other and did not have
to live in fear. Can we have this time back, please?

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The activities leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 284709 - project 'FuturICT', a Coordination and Support Action in the Information and Communication Technologies activity area